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Lembaga Penelitian Pengabdian Masyarakat Universitas Nusa Mandiri
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KOMPARASI ALGORITMA NAIVE BAYES DAN SUPPORT VECTOR MACHINE UNTUK ANALISA SENTIMEN REVIEW FILM
Keywords:
Analisa Sentimen, Review, SVM, Naive Bayes
Abstract
Film is a subject of interest by a large number of people among the social networking community who have significant differences in their opinions or sentiments. Sentiment analysis or opinion mining is one solution to overcome the problem to classify opinions or reviews into positive or negative opinions automatically. The technique used in this study is Naive Bayes and Support Vector Machines (SVM). Naive Bayes has advantages that are simple, fast and have high accuracy. Whereas SVM is able to identify a separate hyperplane that maximizes the margin between two different classes. The results of the sentiment classification in this study consisted of two class labels, namely positive and negative. The value of accuracy produced will be a benchmark for finding the best testing model for sentiment classification cases. Evaluation is done using 10 fold cross validation. Accuracy measurements were measured by confusion matrix and ROC curve. The results showed that the accuracy value for the Naive Bayes algorithm was 84.50%. While the accuracy value of the Support Vector Machine (SVM) algorithm is greater than Naive Bayes which is equal to 90.00%.
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References
Aulianita, R. (2016). Komparasi Metode K-Nearest Neighbors dan Support Vector Machine Pada Sentiment Analysis Review Kamera, 8(3), 71–77.
Dhande, L. L., & Patnaik, P. G. K. (2014). Analyzing Sentiment of Movie Review Data using Naive Bayes Neural Classifier. International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), 3(4), 313–320.
Haddi, E., Liu, X., & Shi, Y. (2013). The Role of Text Pre-processing in Sentiment Analysis. First International Conference on Information Technology and Quantitative Management, 17, 26–32. https://doi.org/10.1016/j.procs.2013.05.05.
Indrayuni, E. (2018). Laporan Akhir Penelitian Mandiri 2018.
Medhat, W., Hassan, A., & Korashy, H. (2014). Sentiment analysis algorithms and applications: A survey. Ain Shams Engineering Journal. https://doi.org/10.1016/j.asej.2014.04.011.
Moraes, R., Valiati, J. F., & Gavião Neto, W. P. (2013). Document-level sentiment classification: An empirical comparison between SVM and ANN. Expert Systems with Applications, 40(2), 621–633. https://doi.org/10.1016/j.eswa.2012.07.05.
Samad, A., Basari, H., Hussin, B., Pramudya, I. G., & Zeniarja, J. (2013). Opinion Mining of Movie Review using Hybrid Method of Support Vector Machine and Particle Swarm Optimization. Procedia Engineering, 53, 453–462. https://doi.org/10.1016/j.proeng.2013.02.059.
Zhang, L., Hua, K., Wang, H., Qian, G., & Zheng, L. (2014). Sentiment analysis on reviews of mobile users. Procedia Computer Science, 34, 458–465. https://doi.org/10.1016/j.procs.2014.07.013
Dhande, L. L., & Patnaik, P. G. K. (2014). Analyzing Sentiment of Movie Review Data using Naive Bayes Neural Classifier. International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), 3(4), 313–320.
Haddi, E., Liu, X., & Shi, Y. (2013). The Role of Text Pre-processing in Sentiment Analysis. First International Conference on Information Technology and Quantitative Management, 17, 26–32. https://doi.org/10.1016/j.procs.2013.05.05.
Indrayuni, E. (2018). Laporan Akhir Penelitian Mandiri 2018.
Medhat, W., Hassan, A., & Korashy, H. (2014). Sentiment analysis algorithms and applications: A survey. Ain Shams Engineering Journal. https://doi.org/10.1016/j.asej.2014.04.011.
Moraes, R., Valiati, J. F., & Gavião Neto, W. P. (2013). Document-level sentiment classification: An empirical comparison between SVM and ANN. Expert Systems with Applications, 40(2), 621–633. https://doi.org/10.1016/j.eswa.2012.07.05.
Samad, A., Basari, H., Hussin, B., Pramudya, I. G., & Zeniarja, J. (2013). Opinion Mining of Movie Review using Hybrid Method of Support Vector Machine and Particle Swarm Optimization. Procedia Engineering, 53, 453–462. https://doi.org/10.1016/j.proeng.2013.02.059.
Zhang, L., Hua, K., Wang, H., Qian, G., & Zheng, L. (2014). Sentiment analysis on reviews of mobile users. Procedia Computer Science, 34, 458–465. https://doi.org/10.1016/j.procs.2014.07.013
Published
2018-09-15
How to Cite
Indrayuni, E. (2018). KOMPARASI ALGORITMA NAIVE BAYES DAN SUPPORT VECTOR MACHINE UNTUK ANALISA SENTIMEN REVIEW FILM. Jurnal Pilar Nusa Mandiri, 14(2), 175-180. https://doi.org/10.33480/pilar.v14i2.36
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